Review on Prediction of Diabetes Using Machine Learning Classification Algorithms

Diabetes is a global health situation that can impact a patient's whole life. Diabetes affects people of every age group. Developing technology offers a novel technique to predict diabetes and improve efficiency. Researchers mostly take the Pima Indian dataset to predict diabetes. In this study, the authors construct a structure, which can accurately evaluate the chance of diabetes in patients. This research presents a framework for accurately estimating the chance of diabetes in patients. The authors propose using Machine Learning techniques like Decision Trees, SVM, and Naive Bayes to diagnose diabetes in its early stages. The Pima Indian Diabetes test from the UCI library is utilized to predict diabetes, saving time and ensuring accuracy. Key Words: Machine Learning, Decision Tree, Naïve Bayes, Diabetes, Precision, Classification, SVM.